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"Polylactic acid"

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"Polylactic acid"

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A Study on the Wear Phenomena of PLA and PETG Materials for 3D Printing in Non-lubricated Condition
Yonsang Cho, Hyunseop Lee
J. Korean Soc. Precis. Eng. 2024;41(2):145-151.
Published online February 1, 2024
DOI: https://doi.org/10.7736/JKSPE.023.119
With the recent development of 3D printing technology, various 3D printing materials have been developed and used. To utilize 3D-printed products with mechanical parts, studies on friction and wear characteristics according to relative motion between materials are required. However, tribology studies on 3D-printed materials are limited compared to those of the existing materials for mechanical parts. In this study, the frictional and wear characteristics are identified through a reciprocating wear test in non lubricated conditions between the Polylactic Acid (PLA) and Polyethylene Terephthalate Glycol (PETG) printed in the Fused Deposition Modeling (FDM) method. In the wear test between the same materials, the friction coefficient and wear rate were higher in the PLA than in the PETG, and PLA was deposited on the block due to high frictional heat. In the wear test of the PLA block and PETG bump, the wear of the PLA block decreased compared to the wear test between the same materials, but the wear of the PETG bump tended to increase. Therefore, it seems that the 3D-printed PETG may be more advantageous in terms of friction and wear than 3D-printed PLA during relative movement in a non lubricating condition.

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  • Tribological Properties of Fused Deposition Modeling-Printed Polylactic Acid and PLA-CF: Extrusion Temperature and Internal Structure
    Paweł Zawadzki, Justyna Rybarczyk, Adam Patalas, Natalia Wierzbicka, Remigiusz Łabudzki, Băilă Diana, Fodchuk Igor, Bonilla Mirian
    Journal of Tribology.2026;[Epub]     CrossRef
  • Artificial Intelligence Technologies and Applications in Additive Manufacturing
    Selim Ahamed Shah, In Hwan Lee, Hochan Kim
    International Journal of Precision Engineering and Manufacturing.2025; 26(9): 2463.     CrossRef
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Effect of Process Parameters on Mechanical Strength of Fabricated Parts using the Fused Deposition Modelling Method
Lan P. T., Huy A. Nguyen, Huy Q. Nguyen, Loc K. H., Thanh T. Tran
J. Korean Soc. Precis. Eng. 2019;36(8):705-712.
Published online August 1, 2019
DOI: https://doi.org/10.7736/KSPE.2019.36.8.705
This study investigated the effects of process parameters on mechanical properties of fabricated parts of the Polylactic acid (PLA) materials using fused deposition modeling (FDM) in 3D printing Technology. First, Taguchi method in the design of experiment (DOE) approach was applied to generate a design matrix of three process parameters namely; printing speed, extrusion temperature and layer thickness. A L9 array with 9 specimens was used for fabrication under various process parameters by the Builder 3D printer. Tensile test was implemented and recorded in accordance with ASTM D368 standard. Achieved data were analyzed using the Minitab software to show the effect of each process parameter on mechanical properties. Secondly, a regression model was developed to predict the trend of response in case of change in setting of parameters and estimating the optimal set of process parameters which creates the strongest FDM parts. The achieved optimum parameters were used to validate the fabricated samples for tensile testing. According to the results, the best mechanical strength of fabricated parts was achieved with printing speed of 48 mm/s, extrusion temperature of 220 degree of celsius (C) and the layer thickness of 0.15 mm. Also, the extrusion temperature was the most influencing factor on ultimate tensile stress.

Citations

Citations to this article as recorded by  Crossref logo
  • Predicting the dynamic tensile response of FDM materials using machine learning
    Amjad Alsakarneh, Sinan Obaidat, Ahmad A. Mumani, Mohammad F. Tamimi
    Discover Applied Sciences.2025;[Epub]     CrossRef
  • From feedforward to quantum: Exploring neural networks for predicting tensile strength in additively manufactured polylactic acid parts
    Mohammad Hossein Nikzad, Mohammad Heidari-Rarani, Reza Rasti, Neda Moghim, Sachin Shetty
    Materials Today Communications.2025; 49: 113956.     CrossRef
  • Machine learning-driven prediction of tensile strength in 3D-printed PLA parts
    Mohammad Hossein Nikzad, Mohammad Heidari-Rarani, Reza Rasti, Pooya Sareh
    Expert Systems with Applications.2025; 264: 125836.     CrossRef
  • Using Bayesian Regularized Artificial Neural Networks to Predict the Tensile Strength of Additively Manufactured Polylactic Acid Parts
    Valentina Vendittoli, Wilma Polini, Michael S. J. Walter, Stefan Geißelsöder
    Applied Sciences.2024; 14(8): 3184.     CrossRef
  • Experimental and Investigation of ABS Filament Process Variables on Tensile Strength Using an Artificial Neural Network and Regression Model
    Mostafa Adel Abdullah Hamed
    Al-Nahrain Journal for Engineering Sciences.2024; 27(2): 251.     CrossRef
  • OPTIMIZATION OF FDM 3D PRINTING PARAMETERS FOR TENSILE STRENGTH OF PETG CARBON FIBRE USING TAGUCHI METHOD
    Nor Aiman Sukindar, Nurul Aini Athirah Abdul Rahim , Ahmad Shah Hizam Md Yasir , Shafie Kamaruddin , Mohamad Talhah Al Hafiz Mohd Khata , Nor Farah Huda Abd Halim , Mohamad Nor Hafiz Jamil , Ahmad Azlan Ab Aziz
    International Journal of Modern Manufacturing Technologies.2024; 16(3): 143.     CrossRef
  • The use of machine learning in process–structure–property modeling for material extrusion additive manufacturing: a state-of-the-art review
    Ziadia Abdelhamid, Habibi Mohamed, Sousso Kelouwani
    Journal of the Brazilian Society of Mechanical Sciences and Engineering.2024;[Epub]     CrossRef
  • Machine Learning Study of the Effect of Process Parameters on Tensile Strength of FFF PLA and PLA-CF
    Abdelhamid Ziadia, Mohamed Habibi, Sousso Kelouwani
    Eng.2023; 4(4): 2741.     CrossRef
  • Metatarsal bone model production using 3D printing and comparison of material properties with results obtained from CT-based modeling and real bone
    Zeliha Coşkun, Talip Çelik, Yasin Kişioğlu
    Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine.2023; 237(4): 481.     CrossRef
  • Ergiyik filament ile imalat yönteminde kullanılan PLA ve çelik katkılı PLA filament malzemelerin mekanik ve fiziksel özelliklerinin incelenmesi
    Ali Osman ER, Osman Muhsin AYDINLI
    Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi.2023; 39(2): 1285.     CrossRef
  • INFLUENCE OF FDM PROCESS VARIABLES' ON TENSILE STRENGTH, WEIGHT, AND ACTUAL PRINTING TIME WHEN USING ABS FILAMENT
    Tahseen Fadhil Abbas, Ali Hind Basil , Kalida Kadhim Mansor
    International Journal of Modern Manufacturing Technologies.2022; 14(1): 7.     CrossRef
  • Analysis of Correlation between FDM Additive and Finishing Process Conditions in FDM Additive-Finishing Integrated Process for the Improved Surface Quality of FDM Prints
    Ji Won Yu, Hyung Jin Jeong, Jae Hyung Park, Dong Hun Lee
    Journal of the Korean Society for Precision Engineering.2022; 39(2): 159.     CrossRef
  • Regression Model for Optimization and Prediction of Tensile Strength of a PLA Prototype Printed
    Lahcen Hamouti, Omar El Farissi, Omar Outemssa
    Journal of Advanced Computational Intelligence and Intelligent Informatics.2022; 26(6): 952.     CrossRef
  • Effect of extruder temperature and printing speed on the tensile strength of fused deposition modeling (FDM) 3D printed samples: a meta-analysis study
    Sajjad Farashi, Fariborz Vafaee
    International Journal on Interactive Design and Manufacturing (IJIDeM).2022; 16(1): 305.     CrossRef
  • Effects of raster angle in single- and multi-oriented layers for the production of polyetherimide (PEI/ULTEM 1010) parts with fused deposition modelling
    Musa Yilmaz, Necip Fazil Yilmaz
    Materials Testing.2022; 64(11): 1651.     CrossRef
  • Optimisation of Strength Properties of FDM Printed Parts—A Critical Review
    Daniyar Syrlybayev, Beibit Zharylkassyn, Aidana Seisekulova, Mustakhim Akhmetov, Asma Perveen, Didier Talamona
    Polymers.2021; 13(10): 1587.     CrossRef
  • Influence of 3D printing process parameters on the mechanical properties and mass of PLA parts and predictive models
    João Araújo Afonso, Jorge Lino Alves, Gabriela Caldas, Barbara Perry Gouveia, Leonardo Santana, Jorge Belinha
    Rapid Prototyping Journal.2021; 27(3): 487.     CrossRef
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